| Signal | R1 0528 | Delta | GLM 4.6 |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 80 | +9 | |
Pricing | 2 | +0 | |
Context window size | 83 | -1 | |
Recency | 77 | -23 | |
Output Capacity | 80 | -8 | |
| Overall Result | 2 wins | of 6 | 3 wins |
30
days higher
0
days
0
days higher
DeepSeek
Zhipu AI
GLM 4.6 saves you $18.50/month
That's $222.00/year compared to R1 0528 at your current usage level of 100K calls/month.
| Metric | R1 0528 | GLM 4.6 | Winner |
|---|---|---|---|
| Overall Score | 79 | 71 | R1 0528 |
| Rank | #29 | #55 | R1 0528 |
| Quality Rank | #29 | #55 | R1 0528 |
| Adoption Rank | #29 | #55 | R1 0528 |
| Parameters | -- | -- | -- |
| Context Window | 164K | 205K | GLM 4.6 |
| Pricing | $0.45/$2.15/M | $0.39/$1.90/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | R1 0528 |
| Benchmarks | 80 | 70 | R1 0528 |
| Pricing | 2 | 2 | R1 0528 |
| Context window size | 83 | 84 | GLM 4.6 |
| Recency | 77 | 99 | GLM 4.6 |
| Output Capacity | 80 | 89 | GLM 4.6 |
Our score (0-100) is driven by benchmark performance (90%) from LMArena Elo, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Here's what the scores mean for these two models:
Scores 79/100 (rank #29), placing it in the top 90% of all 290 models tracked.
Scores 71/100 (rank #55), placing it in the top 81% of all 290 models tracked.
R1 0528 has a 8-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
GLM 4.6 offers 12% better value per quality point. At 1M tokens/day, you'd spend $34.35/month with GLM 4.6 vs $39.00/month with R1 0528 - a $4.65 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. GLM 4.6 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (205K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.90/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (79/100) correlates with better nuance, coherence, and style in long-form content
R1 0528 has a moderate advantage with a 8.299999999999997-point lead in composite score. It wins on more signal dimensions, but GLM 4.6 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
R1 0528
Marginally better benchmark scores; both are excellent
Best for Cost
GLM 4.6
12% lower pricing; better value at scale
Best for Reliability
R1 0528
Higher uptime and faster response speeds
Best for Prototyping
R1 0528
Stronger community support and better developer experience
Best for Production
R1 0528
Wider enterprise adoption and proven at scale
by DeepSeek
| Capability | R1 0528 | GLM 4.6 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
DeepSeek
Zhipu AI
GLM 4.6 saves you $0.4080/month
That's 12% cheaper than R1 0528 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | R1 0528 | GLM 4.6 |
|---|---|---|
| Context Window | 164K | 205K |
| Max Output Tokens | 65,536 | 204,800 |
| Open Source | Yes | Yes |
| Created | May 28, 2025 | Sep 30, 2025 |
R1 0528 scores 79/100 (rank #29) compared to GLM 4.6's 71/100 (rank #55), giving it a 8-point advantage. R1 0528 is the stronger overall choice, though GLM 4.6 may excel in specific areas like cost efficiency.
R1 0528 is ranked #29 and GLM 4.6 is ranked #55 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from LMArena, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
GLM 4.6 is cheaper at $1.90/M output tokens vs R1 0528's $2.15/M output tokens - 1.1x more expensive. Input token pricing: R1 0528 at $0.45/M vs GLM 4.6 at $0.39/M.
GLM 4.6 has a larger context window of 204,800 tokens compared to R1 0528's 163,840 tokens. A larger context window means the model can process longer documents and conversations.